Bioelectric signals within human body control vital human functions. Abnormal variation in these bioelectric signals would impact human health, e.g. leading to deadly conditions such as cardiac arrythmias. The present state of bioelectric signal monitoring relies on microsensors and actuators placed on soft substrates which helps in local data collection but requires external computing devices connected by leads to make interpretation which is both time consuming and bulky.
Researchers at George Washington university have developed a novel idea to incorporate data interpretation, decision making, and generation of bioelectric signals locally using a network of computing chiplets. These chiplets can be realized using existing seminconductor technology or can incorporate new types of devices such as memristors (resistive switches) to increase the compactness and energy efficiency. This implementation has the added advantage of incorporating an artificial neural network in an implantable system in a power and area efficient manner.
Applications
- Real time bio-signal monitoring and data interpretation
- Possible implementation of neural networks
Advantage
- Compact size
- Energy Efficient
- Real time monitoring
- Cost effective
- Reduces time between detection and treatment
